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Found 6 papers, 6 papers with code
Robust Burned Area Delineation through Multitask Learning
In this dataset, we provide annotations for multiple tasks, including burned area delineation and land cover segmentation.
A Multimodal Supervised Machine Learning Approach for Satellite-based Wildfire Identification in Europe
The increasing frequency of catastrophic natural events, such as wildfires, calls for the development of rapid and automated wildfire detection systems.
Land Cover Segmentation with Sparse Annotations from Sentinel-2 Imagery
Land cover (LC) segmentation plays a critical role in various applications, including environmental analysis and natural disaster management.
MMFlood: A Multimodal Dataset for Flood Delineation From Satellite Imagery
To provide baseline performances on the MMFlood test set, we conduct a number of experiments of the flood delineation task using state-of-art deep learning models, and we evaluate the performance gains of entropy-based sampling and multi-encoder architectures, which are respectively used to tackle two of the main challenges posed by MMFlood, namely the class unbalance and the multimodal setting.
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A Contrastive Distillation Approach for Incremental Semantic Segmentation in Aerial Images
Incremental learning represents a crucial task in aerial image processing, especially given the limited availability of large-scale annotated datasets.
To Charge or to Sell? EV Pack Useful Life Estimation via LSTMs, CNNs, and Autoencoders
The customer can then decide to sell the battery when it still has a value, i. e., before it exceeds the end of life of the target application, so it can still be reused in a second domain without compromising safety and reliability.
